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ADEEL ABBAS — Fri, 02 Jan 2026 16:42:33 +0000

Automated Reporting System

ADEEL ABBAS ・ Dec 31 '25

#aws #lambda #s3 #awscommunitybuilder

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ADEEL ABBAS — Thu, 01 Jan 2026 06:22:03 +0000

Automated Reporting System

ADEEL ABBAS ・ Dec 31 '25

#aws #lambda #s3 #awscommunitybuilder

Automated Reporting System

ADEEL ABBAS — Wed, 31 Dec 2025 15:49:13 +0000

Overview
We’ll build a system using AWS Lambda and other serverless tools to automate daily reporting. The system will:

Collect data from multiple sources.
Generate a PDF report.
Send the report via email.
Trigger this process daily.

This guide assumes you have a basic understanding of AWS. Let’s start!

Step 1: Create an S3 Bucket

Go to the S3 service.
Click Create bucket.
Name your bucket (e.g., daily-reports-s3-bucket).
Keep other settings default and click Create.
This bucket will store the reports if needed.

Step 2: Verify an Email Address in SES

Go to Amazon SES.
Navigate to Email Addresses under Identity Management.
Click Verify a New Email Address and enter your email.
Check your email inbox and click the verification link.

This allows SES to send emails from this address.

Step 3: Write the Lambda Function

Go to AWS Lambda and click the Create function.
Choose:

Author from scratch.
Function name: daily-report-lambda.
Runtime: Python 3.9 (or later).
Click the Create function.

Code for the Lambda Function

Scroll to the Code section.
Replace the default code with the following:

import boto3
from fpdf import FPDF
import os
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.mime.base import MIMEBase
from email import encoders

def lambda_handler(event, context):
    try:
        # Generate the PDF report
        pdf = FPDF()
        pdf.add_page()
        pdf.set_font("Arial", size=12)
        pdf.cell(200, 10, txt="Daily Report", ln=True, align="C")
        pdf.cell(200, 10, txt="This is your automated report.", ln=True)

        # Save the PDF
        report_path = "/tmp/daily_report.pdf"
        pdf.output(report_path)

        # Upload to S3 (Optional)
        s3 = boto3.client('s3')
        bucket_name = "daily-reports-s3-bucket"
        s3.upload_file(report_path, bucket_name, "daily_report.pdf")

        # Send email via SES with attachment using raw email
        ses = boto3.client('ses')
        msg = MIMEMultipart()
        msg['From'] = "sender_email@gmail.com"  # Replace with your SES verified email
        msg['To'] = "receiver_email@gmail.com"  # Replace with recipient email
        msg['Subject'] = "Daily Report"

        # Attach the text body
        body = MIMEText("Please find the attached report.", 'plain')
        msg.attach(body)

        # Attach the PDF report
        with open(report_path, 'rb') as file:
            part = MIMEBase('application', 'octet-stream')
            part.set_payload(file.read())
            encoders.encode_base64(part)
            part.add_header('Content-Disposition', f'attachment; filename={os.path.basename(report_path)}')
            msg.attach(part)

        # Send the email using SES's send_raw_email
        response = ses.send_raw_email(
            Source=msg['From'],
            Destinations=[msg['To']],
            RawMessage={'Data': msg.as_string()}
        )

        return {"status": "success", "response": response}

    except Exception as e:
        return {"status": "error", "message": str(e)}

Step 4: Install Libraries Locally and Deploy (Optional)

You will use third-party libraries like fpdf, as fpdf is not available in Lambda, package them locally:
Install fpdf locally:

pip install fpdf
Zip the files and upload them to the Lambda function.

Step 5: Set Up EventBridge Trigger

Go to EventBridge.
Click Create rule.
Name: daily-report-trigger.
Define pattern: Schedule.
Cron expression: "cron(0 9 * * ? *)" (9:00 AM UTC daily).
Under Target, choose your Lambda function (daily-report-lambda).
Click Create.

Step 6: Test the Lambda Function

Go to the Test tab in your Lambda function.
Create a new test event (leave it blank).
Click Test.
Check your email inbox for the report.

Complete!

You’ve built a serverless reporting system! 🎉

Happy Cloud Learning

Adeel Abbas

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ADEEL ABBAS — Sun, 28 Dec 2025 10:56:41 +0000

Restrict IAM User Access after AWS Budget Limit is reached

ADEEL ABBAS ・ Dec 25 '25

#lambda #aws #iam #awsbilling

Restrict IAM User Access after AWS Budget Limit is reached

ADEEL ABBAS — Thu, 25 Dec 2025 11:27:16 +0000

💰 Automatically Restrict IAM User Access After AWS Budget Limit is Reached

At 2:37 AM, the AWS bill silently crossed its limit, no alarms, no humans watching.
Seconds later, an unseen Lambda woke up, and just like that, the IAM user’s access vanished mid-click.
The cloud didn’t crash, it locked the door 🔒

🎯Goal

Set a spend limit (budget) in AWS.
Send an alert using Amazon SNS when the limit is reached.
Trigger an AWS Lambda function that will restrict an IAM user.
The IAM user will lose AWS access automatically when the budget is exceeded.

✅ Prerequisites

Basic AWS Account
IAM user to test
IAM permissions to create budgets, Lambda functions, and SNS topics

🔧 Step 1: Create an AWS Budget

Go to the AWS Console, choose Billing, then Budgets.
Click Create Budget name: Cost Budget.
Spend limit (let $10 per month).
Add an alert threshold at 100% of the budget.
Create a new SNS Topic when prompted (we'll configure later).

🛠️ Example:

Budget: $10/month
Alert at: 100%

🔔 Step 2: Create an SNS Topic

Go to Amazon SNS choose Topics then Create Topic.
Choose Standard Topic.
Set the name (let: BudgetExceedTopic).
Click Create Topic.
Subscribe Lambda to SNS
We will will link this SNS topic to a Lambda function in the next step.

🖥️ Step 3: Create a Lambda Function

Go to Lambda → Create Function → Author from scratch.
Function name: RestrictIAMUserFunction
Runtime: Python 3.12 (or latest)

Paste This Code:

import boto3
import json

iam = boto3.client('iam')

def lambda_handler(event, context):
    user_name = 'adeel'  # Change this to your IAM username

    deny_policy = {
        "Version": "2012-10-17",
        "Statement": [{
            "Effect": "Deny",
            "Action": "*",
            "Resource": "*"
        }]
    }

    iam.put_user_policy(
        UserName=user_name,
        PolicyName='DenyAllPolicy',
        PolicyDocument=json.dumps(deny_policy)
    )

    return {"status": f"Permissions restricted for user {user_name}"}

🔒 Step 4: Add IAM Permissions to Lambda

The Lambda needs permissions to:
Write logs
Attach IAM policies Inline Policy to Add:

👉 Replace YOUR_ACCOUNT_ID With your AWS Account ID.
If you want to restrict all users, use:
"Resource": "arn:aws:iam::YOUR_ACCOUNT_ID:user/*"

🔗 Step 5: Connect SNS to Lambda

Go to your SNS Topic, choose Subscriptions, then Create Subscription.
Choose Protocol: AWS Lambda.
Choose the Lambda function we just created.
Confirm subscription.

✔️ Now, when the budget threshold is exceeded, SNS will automatically trigger the Lambda function.

✅ Step 6: Review and Test

Budget Alerts should now trigger your SNS topic when the budget is crossed.
SNS will trigger the Lambda function.
Lambda will restrict the IAM user by attaching a deny-all policy.

✔️ You can verify this by checking the user in IAM ( Inline Policies )

🔥 Key Tips

AWS Budgets update a few times a day, so the restriction is not instant, but timely.
Always test on a non-production user first.
You can enhance this by making the Lambda dynamically read the username from the SNS message.

✨ Happy Cloud Learning!

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